9 February 2018 Boundary connectedness-based salient video object segmentation
Author Affiliations +
J. of Electronic Imaging, 27(5), 051206 (2018). doi:10.1117/1.JEI.27.5.051206
One of the most challenging tasks in computer vision is to emulate human cognitive ability to extract the salient object in a scene. We tackle the task of unsupervised salient video object segmentation using boundary connectedness and space-time salient regions. First, boundary prior measure is used to separate salient regions detected in both space and time. Then, background-foreground regions connectedness is computed and combined with appearance model via an iterative energy minimization framework to segment the salient moving object. For temporal consistency, the segmentation result of the current frame is used in addition to the optical flow and the boundary prior to segmenting the next frame. The experiments show a good performance of our algorithm for salient video object segmentation on benchmark datasets even in the presence of different challenges.
© 2018 SPIE and IS&T
Hiba Ramadan, Hamid Tairi, "Boundary connectedness-based salient video object segmentation," Journal of Electronic Imaging 27(5), 051206 (9 February 2018). https://doi.org/10.1117/1.JEI.27.5.051206 Submission: Received 26 September 2017; Accepted 19 January 2018
Submission: Received 26 September 2017; Accepted 19 January 2018

Image segmentation


Optical flow

Image processing algorithms and systems

Binary data

Motion models


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